STAT 4293
Applied Statistics Methods with R
Data input and manipulation in R. Basic R programming. Visualization. Simulation of random variables. Simulation experiments to evaluate estimators and tests. Using optimization to fit models. Data smoothing with splines and kernel density estimation. Bootstrapping and other resampling methods. Data analysis will be undertaken by means of R packages and R programming.
Prerequisites & course information
Prerequisite : STAT 2593 (at least B) or STAT 3093 .
Sources
- Course catalogue ↗2026-2027